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All Blog Posts Tagged 'predictive modeling' (140)

Misuses of Statistics: Examples and Solutions

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, dataviz, and many more. To keep receiving these articles, …

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Added by Vincent Granville on September 1, 2019 at 9:30am — No Comments

Learning Machine Learning: A Personal Journey

Who wants to hear a story about data?!

...(silence)...

Understandably, not a lot of people would raise their hands to an intro like that. For me, however, data has sculpted my career path and led to many exciting opportunities over the life of my profession. It hasn't been easy -- I think any entrepreneur would tell you the same and surely the content and media attention around self-starting individuals would concur. But I'm not here to tell you about the hardships of…

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Added by John E Sukup on December 11, 2018 at 3:00am — No Comments

Reducing bias and ensuring fairness in data science

Blog post by Henry Hinnefield, Lead Data Scientist at Civis Analytics

"When machine learning models make decisions that affect people’s lives, how can you be sure those decisions are fair?"

In our work at Civis, we build a lot of models. Most…

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Added by Civis Analytics on April 3, 2018 at 6:30pm — 1 Comment

18 Great Articles About Predictive Analytics

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting,…

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Added by Vincent Granville on March 13, 2018 at 5:30pm — No Comments

26 Great Articles and Tutorials about Regression Analysis

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, ouliers, regression Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign…

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Added by Vincent Granville on February 10, 2018 at 10:30am — No Comments

Thursday News: ML, Marketing Bots, Time Series, AI, Predictive Modeling, Spark, Scala

Here is our selection of featured articles and resources posted since Monday:

Technical Resources

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Added by Vincent Granville on February 8, 2018 at 10:00am — No Comments

Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering

Description

The disciplines of science and engineering rely heavily on the forecasting of prospective constraints for concepts that have not yet been proven to exist, especially in areas such as artificial intelligence. Obtaining quality solutions to the problems presented becomes increasingly difficult due to the number of steps required to sift through the possible solutions, and the ability to solve such problems relies on the recognition of…

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Added by Sanjiban Sekhar Roy on February 3, 2018 at 9:30am — No Comments

Book: Predictive Modeling and Optimization Methods in Science and Engineering

Our edited book entitled as "Predictive Modeling and Optimization Methods in Science and Engineering ", IGI Global (Editors: Dookie Kim- South Korea, Sanjiban Sekhar Roy -India,Tim Länsivaara -Finland, Ravinesh Deo-Australia,Pijush Samui-India) will be available online very soon.Hope this book will help research scholar and machine learning enthusiasts working on predictive models.

To contribute a chapter, click …

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Added by Sanjiban Sekhar Roy on December 21, 2017 at 9:00pm — No Comments

Sample Job Titles and Salaries for Recently filled Data Science Positions in US

This came in my mailbox today, sent from this source. I thought you would be interested in this.

Sample list of recent placement:

Digital, Marketing & Customer Analytics…
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Added by Vincent Granville on November 28, 2017 at 1:30pm — No Comments

Data Science of Digital Payments

Abstract – Any one working within industries like the mobility, fintech, mobile money, payments, banking or InsureTech with little knowledge of data science is actually sitting on gold mine to explore and show what Data Science / AI can do for that company. For example by identifying new areas for innovative value creation through data science. Today every…

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Added by Vinod Sharma on October 2, 2017 at 9:00pm — No Comments

27 Great Articles About Machine Learning Algorithms

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, dataviz, AI and…

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Added by Vincent Granville on September 28, 2017 at 3:30pm — 1 Comment

AI and ML in 2017

This article was written by Carlos Mendoza.

Advancements in machine learning and artificial intelligence (AI) opens new doors for…

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Added by Amelia Matteson on September 21, 2017 at 11:00am — No Comments

Neural Networks: Crash Course On Multi-Layer Perceptron

This article was written by Jason Brownlee.

Artificial neural networks are a fascinating area of study, although they can be intimidating when just getting started. There are a lot of specialized terminology used when describing the data structures and algorithms used in the field. …

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Added by Amelia Matteson on August 11, 2017 at 9:00am — No Comments

The 4 Types of Data Analytics

This article was written by Thomas Maydon. Maydon is the Head of Credit Solutions at Principa and has primarily been involved in consulting, analytics, credit bureau and predictive modeling services.Diagram and explanation of the 4 types of data analytics

Simplistically, analytics can be divided into four key categories. I'll explain these four in more detail…

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Added by Amelia Matteson on August 7, 2017 at 11:30am — No Comments

How Big Data Helps Fight Climate Change

This article was written by Hannah Augur.

Global warming. For a topic as massive, important, and (somehow) controversial, big data is a clear option for sorting through the muck. What information is reliable? What solutions are realistic? When a global…

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Added by Amelia Matteson on July 17, 2017 at 10:30am — 1 Comment

13 Great Articles from AnalyticBridge

AnalyticBridge is one of Data Science Central channels. Below is a selection of popular articles posted a while back:

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Added by Vincent Granville on May 31, 2017 at 8:28am — No Comments

Loan Prediction – Using PCA and Naive Bayes Classification with R

Overview

Nowadays, there are numerous risks related to bank loans both for the banks and the borrowers getting the loans. The risk analysis about bank loans needs understanding about the risk and the risk level. Banks need to analyze their customers for loan eligibility so that they can specifically target those customers.

Banks wanted to automate the loan eligibility process (real time) based on customer details such as Gender, Marital Status, Age,…

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Added by Raghavan Madabusi on May 10, 2017 at 4:30pm — 1 Comment

Introduction to Principal Component Analysis

This formula-free summary provides a short overview about how PCA (principal component analysis) works for dimension reduction, that is, to select k features (also called variables) among a larger set of n features, with k much smaller than n. This smaller set of k features built with PCA is the best subset of k features, in the sense that it minimizes the variance of the residual noise when fitting data to a…

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Added by Vincent Granville on April 26, 2017 at 8:30am — 3 Comments

Customer Churn – Logistic Regression with R

Overview

In the customer management lifecycle, customer churn refers to a decision made by the customer about ending the business relationship. It is also referred as loss of clients or customers. Customer loyalty and customer churn always add up to 100%. If a firm has a 60% of loyalty rate, then their loss or churn rate of customers is 40%. As per 80/20 customer profitability rule, 20% of customers are generating 80% of revenue. So, it is very important…

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Added by Raghavan Madabusi on April 13, 2017 at 6:00pm — 7 Comments

The seven deadly sins of statistical misinterpretation, and how to avoid them

By Winnifred Louis, Associate Professor, Social Psychology, The University of Queensland, and Cassandra Chapman,PhD Candidate in Social Psychology, The University of Queensland.…

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Added by L.V. on March 29, 2017 at 8:30am — No Comments

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